B1 inhomogeneity-corrected T1 mapping and quantitative magnetization transfer imaging via simultaneously estimating Bloch-Siegert shift and magnetization transfer effects.

PURPOSE: To introduce a method of inducing Bloch-Siegert shift and magnetization Transfer Simultaneously (BTS) and demonstrate its utilization for measuring binary spin-bath model parameters free pool spin-lattice relaxation ( T 1 F $$ {T}_1^{\mathrm{F}} $$ ), macromolecular fraction ( f $$ f $$ ), magnetization exchange rate ( k F $$ {k}_{\mathrm{F}} $$ ) and local transmit field ( B 1 + $$ {B}_1^{+} $$ ). THEORY AND METHODS: Bloch-Siegert shift and magnetization transfer is simultaneously induced through the application of off-resonance irradiation in between excitation and acquisition of an RF-spoiled gradient-echo scheme. Applying the binary spin-bath model, an analytical signal equation is derived and verified through Bloch simulations. Monte Carlo simulations were performed to analyze the method's performance. The estimation of the binary spin-bath parameters with B 1 + $$ {B}_1^{+} $$ compensation was further investigated through experiments, both ex vivo and in vivo. RESULTS: Comparing BTS with existing methods, simulations showed that existing methods can significantly bias T 1 $$ {T}_1 $$ estimation when not accounting for transmit B 1 $$ {B}_1 $$ heterogeneity and MT effects that are present. Phantom experiments further showed that the degree of this bias increases with increasing macromolecular proton fraction. Multi-parameter fit results from an in vivo brain study generated values in agreement with previous literature. Based on these studies, we confirmed that BTS is a robust method for estimating the binary spin-bath parameters in macromolecule-rich environments, even in the presence of B 1 + $$ {B}_1^{+} $$ inhomogeneity. CONCLUSION: A method of estimating Bloch-Siegert shift and magnetization transfer effect has been developed and validated. Both simulations and experiments confirmed that BTS can estimate spin-bath parameters ( T 1 F $$ {T}_1^{\mathrm{F}} $$ , f $$ f $$ , k F $$ {k}_{\mathrm{F}} $$ ) that are free from B 1 + $$ {B}_1^{+} $$ bias.

Assessment of Striatal Dopamine Transporter Binding in Individuals With Major Depressive Disorder: In Vivo Positron Emission Tomography and Postmortem Evidence.

Importance: Major depressive disorder (MDD) might involve dopamine (DA) reductions. The DA transporter (DAT) regulates DA clearance and neurotransmission and is sensitive to DA levels, with preclinical studies (including those involving inescapable stressors) showing that DAT density decreases when DA signaling is reduced. Despite preclinical data, evidence of reduced DAT in MDD is inconclusive. Objective: Using a highly selective DAT positron emission tomography (PET) tracer ([11C] altropane), DAT availability was probed in individuals with MDD who were not taking medication. Levels of DAT expression were also evaluated in postmortem tissues from donors with MDD who died by suicide. Design, Setting, and Participants: This cross-sectional PET study was conducted at McLean Hospital (Belmont, Massachusetts) and Massachusetts General Hospital (Boston) and enrolled consecutive individuals with MDD who were not taking medication and demographically matched healthy controls between January 2012 and March 2014. Brain tissues were obtained from the Douglas-Bell Canada Brain Bank. For the PET component, 25 individuals with current MDD who were not taking medication and 23 healthy controls recruited from McLean Hospital were included (all provided usable data). For the postmortem component, 15 individuals with depression and 14 healthy controls were considered. Intervention: PET scan. Main Outcomes and Measures: Striatal and midbrain DAT binding potential was assessed. For the postmortem component, tyrosine hydroxylase and DAT levels were evaluated using Western blots. Results: Compared with 23 healthy controls (13 women [56.5%]; mean [SD] age, 26.49 [7.26] years), 25 individuals with MDD (19 women [76.0%]; mean [SD] age, 26.52 [5.92] years) showed significantly lower in vivo DAT availability in the bilateral putamen and ventral tegmental area (Cohen d range, -0.62 to -0.71), and both reductions were exacerbated with increasing numbers of depressive episodes. Unlike healthy controls, the MDD group failed to show an age-associated reduction in striatal DAT availability, with young individuals with MDD being indistinguishable from older healthy controls. Moreover, DAT availability in the ventral tegmental area was lowest in individuals with MDD who reported feeling trapped in stressful circumstances. Lower DAT levels (and tyrosine hydroxylase) in the putamen of MDD compared with healthy controls were replicated in postmortem analyses (Cohen d range, -0.92 to -1.15). Conclusions and Relevance: Major depressive disorder, particularly with recurring episodes, is characterized by decreased striatal DAT expression, which might reflect a compensatory downregulation due to low DA signaling within mesolimbic pathways.

Magnetic resonance imaging based anatomical assessment of tongue impairment due to amyotrophic lateral sclerosis: A preliminary study.

Amyotrophic Lateral Sclerosis (ALS) is a neurological disorder, which impairs tongue function for speech and swallowing. A widely used Diffusion Tensor Imaging (DTI) analysis pipeline is employed for quantifying differences in tongue fiber myoarchitecture between controls and ALS patients. This pipeline uses both high-resolution magnetic resonance imaging (hMRI) and DTI. hMRI is used to delineate tongue muscles, while DTI provides indices to reveal fiber connectivity within and between muscles. The preliminary results using five controls and two patients show quantitative differences between the groups. This work has the potential to provide insights into the detrimental effects of ALS on speech and swallowing.

Feasibility study of using fall-off gradients of early and late PET scans for proton range verification.

PURPOSE: While positron emission tomography (PET) allows for the imaging of tissues activated by proton beams in terms of monitoring the therapy administered, most endogenous tissue elements are activated by relatively high-energy protons. Therefore, a relatively large distance off-set exists between the dose fall-off and activity fall-off. However, 16 O(p,2p,2n)13 N has a relatively low energy threshold which peaks around 12 MeV and also a residual proton range that is approximately 1 to 2 mm. In this phantom study, we tested the feasibility of utilizing the 13 N production peak as well as the differences in activity fall-off between early and late PET scans for proton range verification. One of the main purposes for this research was developing a proton range verification methodology that would not require Monte Carlo simulations. METHODS AND MATERIALS: Both monoenergetic and spread-out Bragg peak beams were delivered to two phantoms - a water-like gel and a tissue-like gel where the proton ranges came to be approximately 9.9 and 9.1 cm, respectively. After 1 min of postirradiation delay, the phantoms were scanned for a period of 30 min using an in-room PET. Two separate (Early and Late) PET images were reconstructed using two different postirradiation delays and acquisition times; Early PET: 1 min delay and 3 min acquisition, Late PET: 21 min delay and 10 min acquisition. The depth gradients of the PET signals were then normalized and plotted as functions of depth. The normalized gradient of the early PET images was subtracted from that of the late PET images, to observe the 13 N activity distribution in relation to depth. Monte Carlo simulations were also conducted with the same set-up as the measurements stated previously. RESULTS: The subtracted gradients show peaks at 9.4 and 8.6 cm in water-gel and tissue-gel respectively for both pristine and SOBP beams. These peaks are created in connection with the sudden change of 13 N signals with depth and consistently occur 2 mm upstream to where 13 N signals were most abundantly created (9.6 and 8.8 cm in water-gel and tissue-gel, respectively). Monte Carlo simulations provided similar results as the measurements. CONCLUSIONS: The subtracted PET signal gradient peaks and the proton ranges for water-gel and tissue-gel show distance off-sets of 4 to 5 mm. This off-set may potentially be used for proton range verification using only the PET measured data without Monte Carlo simulations. More studies are necessary to overcome various limitations, such as perfusion-driven washout, for the feasibility of this technique in living patients.

Validation of Bayesian analysis of compartmental kinetic models in medical imaging.

INTRODUCTION: Kinetic compartmental analysis is frequently used to compute physiologically relevant quantitative values from time series of images. In this paper, a new approach based on Bayesian analysis to obtain information about these parameters is presented and validated. MATERIALS AND METHODS: The closed-form of the posterior distribution of kinetic parameters is derived with a hierarchical prior to model the standard deviation of normally distributed noise. Markov chain Monte Carlo methods are used for numerical estimation of the posterior distribution. Computer simulations of the kinetics of F18-fluorodeoxyglucose (FDG) are used to demonstrate drawing statistical inferences about kinetic parameters and to validate the theory and implementation. Additionally, point estimates of kinetic parameters and covariance of those estimates are determined using the classical non-linear least squares approach. RESULTS AND DISCUSSION: Posteriors obtained using methods proposed in this work are accurate as no significant deviation from the expected shape of the posterior was found (one-sided P>0.08). It is demonstrated that the results obtained by the standard non-linear least-square methods fail to provide accurate estimation of uncertainty for the same data set (P<0.0001). CONCLUSIONS: The results of this work validate new methods for a computer simulations of FDG kinetics. Results show that in situations where the classical approach fails in accurate estimation of uncertainty, Bayesian estimation provides an accurate information about the uncertainties in the parameters. Although a particular example of FDG kinetics was used in the paper, the methods can be extended for different pharmaceuticals and imaging modalities.

A novel approach to assess the treatment response using Gaussian random field in PET.

PURPOSE: The assessment of early therapeutic response to anticancer therapy is vital for treatment planning and patient management in clinic. With the development of personal treatment plan, the early treatment response, especially before any anatomically apparent changes after treatment, becomes urgent need in clinic. Positron emission tomography (PET) imaging serves an important role in clinical oncology for tumor detection, staging, and therapy response assessment. Many studies on therapy response involve interpretation of differences between two PET images, usually in terms of standardized uptake values (SUVs). However, the quantitative accuracy of this measurement is limited. This work proposes a statistically robust approach for therapy response assessment based on Gaussian random field (GRF) to provide a statistically more meaningful scale to evaluate therapy effects. METHODS: The authors propose a new criterion for therapeutic assessment by incorporating image noise into traditional SUV method. An analytical method based on the approximate expressions of the Fisher information matrix was applied to model the variance of individual pixels in reconstructed images. A zero mean unit variance GRF under the null hypothesis (no response to therapy) was obtained by normalizing each pixel of the post-therapy image with the mean and standard deviation of the pretherapy image. The performance of the proposed method was evaluated by Monte Carlo simulation, where XCAT phantoms (128(2) pixels) with lesions of various diameters (2-6 mm), multiple tumor-to-background contrasts (3-10), and different changes in intensity (6.25%-30%) were used. The receiver operating characteristic curves and the corresponding areas under the curve were computed for both the proposed method and the traditional methods whose figure of merit is the percentage change of SUVs. The formula for the false positive rate (FPR) estimation was developed for the proposed therapy response assessment utilizing local average method based on random field. The accuracy of the estimation was validated in terms of Euler distance and correlation coefficient. RESULTS: It is shown that the performance of therapy response assessment is significantly improved by the introduction of variance with a higher area under the curve (97.3%) than SUVmean (91.4%) and SUVmax (82.0%). In addition, the FPR estimation serves as a good prediction for the specificity of the proposed method, consistent with simulation outcome with ∼1 correlation coefficient. CONCLUSIONS: In this work, the authors developed a method to evaluate therapy response from PET images, which were modeled as Gaussian random field. The digital phantom simulations demonstrated that the proposed method achieved a large reduction in statistical variability through incorporating knowledge of the variance of the original Gaussian random field. The proposed method has the potential to enable prediction of early treatment response and shows promise for application to clinical practice. In future work, the authors will report on the robustness of the estimation theory for application to clinical practice of therapy response evaluation, which pertains to binary discrimination tasks at a fixed location in the image such as detection of small and weak lesion.

Mapping (15)O production rate for proton therapy verification.

PURPOSE: This work was a proof-of-principle study for the evaluation of oxygen-15 ((15)O) production as an imaging target through the use of positron emission tomography (PET), to improve verification of proton treatment plans and to study the effects of perfusion. METHODS AND MATERIALS: Dynamic PET measurements of irradiation-produced isotopes were made for a phantom and rabbit thigh muscles. The rabbit muscle was irradiated and imaged under both live and dead conditions. A differential equation was fitted to phantom and in vivo data, yielding estimates of (15)O production and clearance rates, which were compared to live versus dead rates for the rabbit and to Monte Carlo predictions. RESULTS: PET clearance rates agreed with decay constants of the dominant radionuclide species in 3 different phantom materials. In 2 oxygen-rich materials, the ratio of (15)O production rates agreed with the expected ratio. In the dead rabbit thighs, the dynamic PET concentration histories were accurately described using (15)O decay constant, whereas the live thigh activity decayed faster. Most importantly, the (15)O production rates agreed within 2% (P>.5) between conditions. CONCLUSIONS: We developed a new method for quantitative measurement of (15)O production and clearance rates in the period immediately following proton therapy. Measurements in the phantom and rabbits were well described in terms of (15)O production and clearance rates, plus a correction for other isotopes. These proof-of-principle results support the feasibility of detailed verification of proton therapy treatment delivery. In addition, (15)O clearance rates may be useful in monitoring permeability changes due to therapy.

4D numerical observer for lesion detection in respiratory-gated PET.

PURPOSE: Respiratory-gated positron emission tomography (PET)/computed tomography protocols reduce lesion smearing and improve lesion detection through a synchronized acquisition of emission data. However, an objective assessment of image quality of the improvement gained from respiratory-gated PET is mainly limited to a three-dimensional (3D) approach. This work proposes a 4D numerical observer that incorporates both spatial and temporal informations for detection tasks in pulmonary oncology. METHODS: The authors propose a 4D numerical observer constructed with a 3D channelized Hotelling observer for the spatial domain followed by a Hotelling observer for the temporal domain. Realistic (18)F-fluorodeoxyglucose activity distributions were simulated using a 4D extended cardiac torso anthropomorphic phantom including 12 spherical lesions at different anatomical locations (lower, upper, anterior, and posterior) within the lungs. Simulated data based on Monte Carlo simulation were obtained using geant4 application for tomographic emission (GATE). Fifty noise realizations of six respiratory-gated PET frames were simulated by GATE using a model of the Siemens Biograph mMR scanner geometry. PET sinograms of the thorax background and pulmonary lesions that were simulated separately were merged to generate different conditions of the lesions to the background (e.g., lesion contrast and motion). A conventional ordered subset expectation maximization (OSEM) reconstruction (5 iterations and 6 subsets) was used to obtain: (1) gated, (2) nongated, and (3) motion-corrected image volumes (a total of 3200 subimage volumes: 2400 gated, 400 nongated, and 400 motion-corrected). Lesion-detection signal-to-noise ratios (SNRs) were measured in different lesion-to-background contrast levels (3.5, 8.0, 9.0, and 20.0), lesion diameters (10.0, 13.0, and 16.0 mm), and respiratory motion displacements (17.6-31.3 mm). The proposed 4D numerical observer applied on multiple-gated images was compared to the conventional 3D approach applied on the nongated and motion-corrected images. RESULTS: On average, the proposed 4D numerical observer improved the detection SNR by 48.6% (p < 0.005), whereas the 3D methods on motion-corrected images improved by 31.0% (p < 0.005) as compared to the nongated method. For all different conditions of the lesions, the relative SNR measurement (Gain = SNRObserved/SNRNongated) of the 4D method was significantly higher than one from the motion-corrected 3D method by 13.8% (p < 0.02), where Gain4D was 1.49 ± 0.21 and Gain3D was 1.31 ± 0.15. For the lesion with the highest amplitude of motion, the 4D numerical observer yielded the highest observer-performance improvement (176%). For the lesion undergoing the smallest motion amplitude, the 4D method provided superior lesion detectability compared with the 3D method, which provided a detection SNR close to the nongated method. The investigation on a structure of the 4D numerical observer showed that a Laguerre-Gaussian channel matrix with a volumetric 3D function yielded higher lesion-detection performance than one with a 2D-stack-channelized function, whereas a different kind of channels that have the ability to mimic the human visual system, i.e., difference-of-Gaussian, showed similar performance in detecting uniform and spherical lesions. The investigation of the detection performance when increasing noise levels yielded decreasing detection SNR by 27.6% and 41.5% for the nongated and gated methods, respectively. The investigation of lesion contrast and diameter showed that the proposed 4D observer preserved the linearity property of an optimal-linear observer while the motion was present. Furthermore, the investigation of the iteration and subset numbers of the OSEM algorithm demonstrated that these parameters had impact on the lesion detectability and the selection of the optimal parameters could provide the maximum lesion-detection performance. The proposed 4D numerical observer outperformed the other observers for the lesion-detection task in various lesion conditions and motions. CONCLUSIONS: The 4D numerical observer shows substantial improvement in lesion detectability over the 3D observer method. The proposed 4D approach could potentially provide a more reliable objective assessment of the impact of respiratory-gated PET improvement for lesion-detection tasks. On the other hand, the 4D approach may be used as an upper bound to investigate the performance of the motion correction method. In future work, the authors will validate the proposed 4D approach on clinical data for detection tasks in pulmonary oncology.

Simultaneous 99mTc-MDP/123I-MIBG tumor imaging using SPECT-CT: phantom and constructed patient studies.

PURPOSE: Authors' goal is to evaluate the performance of simultaneous (99m)Tc-MDP/(123)I-MIBG tumor imaging with fast Monte-Carlo (MC) based joint iterative reconstruction as compared to sequential (99m)Tc-MDP and (123)I-MIBG tumor imaging. METHODS: Noise-free (99m)Tc and (123)I SPECT projections were acquired separately using an anthropomorphic torso phantom modified to include a fillable tube around the lungs to mimic ribs. Additionally, (99m)Tc and (123)I projections were acquired separately using a 1-cm spherical "tumor" placed at various distances from one detector. Tumor-present data were generated by adding tumor projections to the torso phantom data, which were scaled to the total counts in typical clinical studies. Twenty-five noise realizations were generated by adding Poisson noise to the projection data for each radionuclide. Dual-radionuclide data were synthesized by summing the (99m)Tc and (123)I projections. Image reconstruction was performed using: (1) SR-OSEM, ordered subset expectation maximization (OSEM) without scatter correction (SC) using single-radionuclide (SR) data; (2) SR-MC-OSEM, OSEM with a fast MC-based SC using SR data; (3) DR-OSEM, OSEM without SC using dual-radionuclide (DR) data; and (4) DR-MC-JOSEM, joint OSEM with a fast MC-based SC using DR data. Ten (99m)Tc-MDP and ten (123)I-MIBG data sets, which had tumors mathematically inserted, were also used to evaluate the performance of authors' approach. For the phantom study, relative bias and relative standard deviation of tumor uptake were computed for each tumor using the tumor uptake in the noise-free single-radionuclide images, which were reconstructed by SR-MC-OSEM, as the gold standard. For both the phantom and constructed patient studies, mean contrast and standard deviation of contrast were computed for each tumor for both the single- and dual-radionuclide images. Additionally, contrast recovery was computed as the ratio between mean contrast and the mean contrast for SR-MC-OSEM. RESULTS: For the phantom study, DR-MC-JOSEM yielded 2.7% on average relative bias of tumor uptake using the images, which were reconstructed from the noise-free SR data with SR-MC-OSEM, as the gold-standard. For both the phantom and constructed patient studies, DR-MC-JOSEM yielded 94.7% and 95.2% tumor contrast recovery on average using SR-MC-OSEM as the reference, in the phantom and constructed patient studies, respectively. DR-MC-JOSEM yielded comparable relative standard deviation of bias and standard deviation of contrast to SR-MC-OSEM. CONCLUSIONS: Simultaneous (99m)Tc-MDP/(123)I-MIBG tumor imaging using authors' dual-radionuclide reconstruction approach yielded comparable image quality to sequential (99m)Tc-MDP and (123)I-MIBG imaging. For patients who need to undergo both scans, authors' approach offers perfectly registered dual-tracer images under identical conditions without compromising image quality, and reduces the imaging cost while increasing patient throughput.

Determination of elemental tissue composition following proton treatment using positron emission tomography.

Positron emission tomography (PET) has been suggested as an imaging technique for in vivo proton dose and range verification after proton induced-tissue activation. During proton treatment, irradiated tissue is activated and decays while emitting positrons. In this paper, we assessed the feasibility of using PET imaging after proton treatment to determine tissue elemental composition by evaluating the resultant composite decay curve of activated tissue. A phantom consisting of sections composed of different combinations of (1)H, (12)C, (14)N, and (16)O was irradiated using a pristine Bragg peak and a 6 cm spread-out Bragg-peak (SOBP) proton beam. The beam ranges defined at 90% distal dose were 10 cm; the delivered dose was 1.6 Gy for the near monoenergetic beam and 2 Gy for the SOBP beam. After irradiation, activated phantom decay was measured using an in-room PET scanner for 30 min in list mode. Decay curves from the activated (12)C and (16)O sections were first decomposed into multiple simple exponential decay curves, each curve corresponding to a constituent radioisotope, using a least-squares method. The relative radioisotope fractions from each section were determined. These fractions were used to guide the decay curve decomposition from the section consisting mainly of (12)C + (16)O and calculate the relative elemental composition of (12)C and (16)O. A Monte Carlo simulation was also used to determine the elemental composition of the (12)C + (16)O section. The calculated compositions of the (12)C + (16)O section using both approaches (PET and Monte Carlo) were compared with the true known phantom composition. Finally, two patients were imaged using an in-room PET scanner after proton therapy of the head. Their PET data and the technique described above were used to construct elemental composition ((12)C and (16)O) maps that corresponded to the proton-activated regions. We compared the (12)C and (16)O compositions of seven ROIs that corresponded to the vitreous humor, adipose/face mask, adipose tissue, and brain tissue with ICRU 46 elemental composition data. The (12)C and (16)O compositions of the (12)C + (16)O phantom section were estimated to within a maximum difference of 3.6% for the near monoenergetic and SOBP beams over an 8 cm depth range. On the other hand, the Monte Carlo simulation estimated the corresponding (12)C and (16)O compositions in the (12)C + (16)O section to within a maximum difference of 3.4%. For the patients, the (12)C and (16)O compositions in the seven ROIs agreed with the ICRU elemental composition data, with a mean (maximum) difference of 9.4% (15.2%). The (12)C and (16)O compositions of the phantom and patients were estimated with relatively small differences. PET imaging may be useful for determining the tissue elemental composition and thereby improving proton treatment planning and verification.

Clinical application of in-room positron emission tomography for in vivo treatment monitoring in proton radiation therapy.

PURPOSE: The purpose of this study is to evaluate the potential of using in-room positron emission tomography (PET) for treatment verification in proton therapy and for deriving suitable PET scan times. METHODS AND MATERIALS: Nine patients undergoing passive scattering proton therapy underwent scanning immediately after treatment with an in-room PET scanner. The scanner was positioned next to the treatment head after treatment. The Monte Carlo (MC) method was used to reproduce PET activities for each patient. To assess the proton beam range uncertainty, we designed a novel concept in which the measured PET activity surface distal to the target at the end of range was compared with MC predictions. The repositioning of patients for the PET scan took, on average, approximately 2 minutes. The PET images were reconstructed considering varying scan times to test the scan time dependency of the method. RESULTS: The measured PET images show overall good spatial correlations with MC predictions. Some discrepancies could be attributed to uncertainties in the local elemental composition and biological washout. For 8 patients treated with a single field, the average range differences between PET measurements and computed tomography (CT) image-based MC results were <5 mm (<3 mm for 6 of 8 patients) and root-mean-square deviations were 4 to 11 mm with PET-CT image co-registration errors of approximately 2 mm. Our results also show that a short-length PET scan of 5 minutes can yield results similar to those of a 20-minute PET scan. CONCLUSIONS: Our first clinical trials in 9 patients using an in-room PET system demonstrated its potential for in vivo treatment monitoring in proton therapy. For a quantitative range prediction with arbitrary shape of target volume, we suggest using the distal PET activity surface.

Monitoring proton radiation therapy with in-room PET imaging.

We used a mobile positron emission tomography (PET) scanner positioned within the proton therapy treatment room to study the feasibility of proton range verification with an in-room, stand-alone PET system, and compared with off-line equivalent studies. Two subjects with adenoid cystic carcinoma were enrolled into a pilot study in which in-room PET scans were acquired in list-mode after a routine fractionated treatment session. The list-mode PET data were reconstructed with different time schemes to generate in-room short, in-room long and off-line equivalent (by skipping coincidences from the first 15 min during the list-mode reconstruction) PET images for comparison in activity distribution patterns. A phantom study was followed to evaluate the accuracy of range verification for different reconstruction time schemes quantitatively. The in-room PET has a higher sensitivity compared to the off-line modality so that the PET acquisition time can be greatly reduced from 30 to <5 min. Features in deep-site, soft-tissue regions were better retained with in-room short PET acquisitions because of the collection of (15)O component and lower biological washout. For soft tissue-equivalent material, the distal fall-off edge of an in-room short acquisition is deeper compared to an off-line equivalent scan, indicating a better coverage of the high-dose end of the beam. In-room PET is a promising low cost, high sensitivity modality for the in vivo verification of proton therapy. Better accuracy in Monte Carlo predictions, especially for biological decay modeling, is necessary.

Dual-radionuclide brain SPECT for the differential diagnosis of parkinsonism.

Parkinsonism is a neurological syndrome characterized by tremor, bradykinesia, rigidity, and postural instability. The underlying causes of parkinsonism are numerous. It is of paramount importance to make clean distinction among these diseases. However, the differential diagnosis of parkinsonism is challenging. Simultaneous dual-radionuclide brain SPECT allows us to assess both blood perfusion and dopamine transporter function under the identical physiological conditions. This approach has been proven to improve the differential diagnosis of parkinsonism. The simultaneous (99m)Tc-ECD/(123)I-FP-CIT brain SPECT protocols, which are used for the differential diagnosis of idiopathic Parkinson's disease and multiple system atrophy as well as corticobasal degeneration and progressive supranuclear palsy, are presented.

Monte Carlo modeling of cascade gamma rays in (86)Y PET imaging: preliminary results.

(86)Y is a PET agent that could be used as an ideal surrogate to allow personalized dosimetry in (90)Y radionuclide therapy. However, (86)Y also emits cascade gamma rays. We have developed a Monte Carlo program based on SimSET (Simulation System for Emission Tomography) to model cascade gamma rays in PET imaging. The new simulation was validated with the GATE simulation package. Agreements within 15% were found in spatial resolution, apparent scatter fraction (ratio of coincidences outside peak regions in line source sinograms), single and coincidence statistics and detected photons energy distribution within the PET energy window. A discrepancy of 20% was observed in the absolute scatter fraction, likely caused by differences in the tracking of higher energy cascade gamma photons. On average, the new simulation is 6 times faster than GATE, and the computing time can be further improved by using variance reduction techniques currently available in SimSET. Comparison with phantom acquisitions showed agreements in spatial resolutions and the general shape of projection profiles; however, the standard scatter correction method on the scanner is not directly applicable to (86)Y PET as it leads to incorrect scatter fractions. The new simulation was used to characterize (86)Y PET. Compared with conventional (18)F PET, in which major contamination at low count rates comes from scattered events, cascade gamma-involved events are more important in (86)Y PET. The two types of contaminations have completely different distribution patterns, which should be considered for the corrections of their effects. Our approach will be further improved in the future in the modeling of random coincidences and tracking of high-energy photons, and simulation results will be used for the development of correction methods in (86)Y PET.

Reproducibility and accuracy of quantitative myocardial blood flow assessment with (82)Rb PET: comparison with (13)N-ammonia PET.

UNLABELLED: (82)Rb cardiac PET allows the assessment of myocardial perfusion with a column generator in clinics that lack a cyclotron. There is evidence that the quantitation of myocardial blood flow (MBF) and coronary flow reserve (CFR) with dynamic (82)Rb PET is feasible. The objectives of this study were to determine the accuracy and reproducibility of MBF estimates from dynamic (82)Rb PET by using our methodology for generalized factor analysis (generalized factor analysis of dynamic sequences [GFADS]) and compartment analysis. METHODS: Reproducibility was evaluated in 22 subjects undergoing dynamic rest and dipyridamole stress (82)Rb PET studies at a 2-wk interval. The inter- and intraobserver variability of MBF quantitation with dynamic (82)Rb PET was assessed with 4 repeated estimations by each of 4 observers. Accuracy was evaluated in 20 subjects undergoing dynamic rest and dipyridamole stress PET studies with (82)Rb and (13)N-ammonia, respectively. The left ventricular and right ventricular blood pool and left ventricular tissue time-activity curves were estimated by GFADS. MBF was estimated by fitting the blood pool and tissue time-activity curves to a 2-compartment kinetic model for (82)Rb and to a 3-compartment model for (13)N-ammonia. CFR was estimated as the ratio of peak MBF to baseline MBF. RESULTS: The reproducibility of the MBF estimates in repeated (82)Rb studies was very good at rest and during peak stress (R(2)= 0.935), as was the reproducibility of the CFR estimates (R(2) = 0.841). The slope of the correlation line was very close to one for the estimation of MBF (0.986) and CFR (0.960) in repeated (82)Rb studies. The intraobserver reliability was less than 3% for the estimation of MBF at rest and during peak stress as well as for the estimation of CFR. The interobserver reliabilities were 0.950 at rest and 0.975 at peak stress. The correlation between myocardial flow estimates obtained at rest and those obtained during peak stress in (82)Rb and (13)N-ammonia studies was very good (R(2) = 0.857). Bland-Altman plots comparing CFR estimated with (82)Rb and CFR estimated with (13)N-ammonia revealed an underestimation of CFR with (82)Rb compared with (13)N-ammonia; the underestimation was within +/-1.96 SD. CONCLUSION: MBF quantitation with GFADS and dynamic (82)Rb PET demonstrated excellent reproducibility as well as intra- and interobserver reliability. The accuracy of the absolute quantitation of MBF with factor and compartment analyses and dynamic (82)Rb PET was very good, compared with that achieved with (13)N-ammonia, for MBF of up to 2.5 mL/g/min.

Quantitative simultaneous 99mTc/123I cardiac SPECT using MC-JOSEM.

Simultaneous rest 99mTc-Sestamibi/ 123I-BMIPP cardiac SPECT imaging has the potential to replace current clinical 99mTc-Sestamibi rest/stress imaging and therefore has great potential in the case of patients with chest pain presenting to the emergency department. Separation of images of these two radionuclides is difficult, however, because their emission energies are close. The authors previously developed a fast Monte Carlo (MC)-based joint ordered-subset expectation maximization (JOSEM) iterative reconstruction algorithm (MC-JOSEM), which simultaneously compensates for scatter and cross talk as well as detector response within the reconstruction algorithm. In this work, the authors evaluated the performance of MC-JOSEM in a realistic population of 99mTc/123I studies using cardiac phantom data on a Siemens e.cam system using a standard cardiac protocol. The authors also compared the performance of MC-JOSEM for estimation tasks to that of two other methods: standard OSEM using photopeak energy windows without scatter correction (NSC-OSEM) and standard OSEM using a Compton-scatter energy window for scatter correction (SC-OSEM). For each radionuclide the authors separately acquired high-count projections of radioactivity in the myocardium wall, liver, and soft tissue background compartments of a water-filled torso phantom, and they generated synthetic projections of various dual-radionuclide activity distributions. Images of different combinations of myocardium wall/background activity concentration ratios for each radionuclide were reconstructed by NSC-OSEM, SC-OSEM, and MC-JOSEM. For activity estimation in the myocardium wall, MC-JOSEM always produced the best relative bias and relative standard deviation compared with NSC-OSEM and SC-OSEM for all the activity combinations. On average, the relative biases after 100 iterations were 8.1% for 99mTc and 3.7% for 123I with MC-JOSEM, 39.4% for 99mTc and 23.7% for 123I with NSC-OSEM, and 20.9% for 99mTc with SC-OSEM. The relative standard deviations after 30 iterations were 0.7% for 99mTc and 1.0% for 123I with MC-JOSEM, as compared to 1.1% for 99mTc and 1.2% for 123I with NSC-OSEM and 1.3% for 99mTc with SC-OSEM. Finally, the authors compared the relative standard deviation after 30 iterations with the minimum theoretical variance on activity estimation, the Cramer-Rao lower bound (CRB), and with the biased CRB. The measured precision was larger than the biased bound values by factors of 2-4, suggesting that further improvement could be made to the method.

Sequential and simultaneous dual-isotope brain SPECT: comparison with PET for estimation and discrimination tasks in early Parkinson disease.

Parkinson disease (PD) is the second most frequently occurring cerebral degenerative disease, after Alzheimer disease. Treatments are available, but their efficacy is diminished unless they are administered in the early stages. Therefore, early identification of PD is crucial. In addition to providing perfectly registered studies, simultaneous 99mTc/123I imaging makes possible the assessment of pre- and postsynaptic neurotransmission functions under identical physiological conditions, while doubling the number of counts for the same total imaging time. These advantages are limited, however, by cross talk between the two radionuclides due to the close emission energies of 99mTc (140 keV) and 123I (159 keV). PET, on the other hand, provides good temporal and spatial resolution and sensitivity but usually requires the use of a single radionuclide. In the present work, the authors compared brain PET with sequential and simultaneous dual-isotope SPECT for the task of estimating striatal activity concentration and striatal size for a normal brain and two stages of early PD. Realistic Monte Carlo simulations of a time-of-flight PET scanner and gamma cameras were performed while modeling all interactions in the brain, collimator (gamma camera) and crystal (detector block in PET), as well as population biological variability of pre- and postsynaptic uptake. For SPECT imaging, we considered two values of system energy resolution and scanners with two and three camera heads. The authors used the Cramer-Rao bound, as a surrogate for the best theoretical performance, to optimize the SPECT acquisition energy windows and objectively compare PET and SPECT. The authors determined the discrimination performance between 500 simulated subjects in every disease stage as measured by the area under the ROC curve (AUC). The discrimination accuracy between a normal subject and a subject in the prodromal disease stage was AUC = 0.924 with PET, compared to 0.863 and 0.831 with simultaneous and sequential SPECT, respectively. The significant improvement in performance obtained with simultaneous dual-isotope SPECT compared to sequential imaging (p = 0.019) was due primarily to the increased number of counts detected and resulted in comparable performance when performing simultaneous SPECT on a two-head camera with 9.2% energy resolution to that obtained with sequential SPECT on a three-head camera with 6.2% energy resolution.

Improved activity estimation with MC-JOSEM versus TEW-JOSEM in 111In SPECT.

We have previously developed a fast Monte Carlo (MC)-based joint ordered-subset expectation maximization (JOSEM) iterative reconstruction algorithm, MC-JOSEM. A phantom study was performed to compare quantitative imaging performance of MC-JOSEM with that of a triple-energy-window approach (TEW) in which estimated scatter was also included additively within JOSEM, TEW-JOSEM. We acquired high-count projections of a 5.5 cm3 sphere of 111In at different locations in the water-filled torso phantom; high-count projections were then obtained with 111In only in the liver or only in the soft-tissue background compartment, so that we could generate synthetic projections for spheres surrounded by various activity distributions. MC scatter estimates used by MC-JOSEM were computed once after five iterations of TEW-JOSEM. Images of different combinations of liver/background and sphere/background activity concentration ratios were reconstructed by both TEW-JOSEM and MC-JOSEM for 40 iterations. For activity estimation in the sphere, MC-JOSEM always produced better relative bias and relative standard deviation than TEW-JOSEM for each sphere location, iteration number, and activity combination. The average relative bias of activity estimates in the sphere for MC-JOSEM after 40 iterations was -6.9%, versus -15.8% for TEW-JOSEM, while the average relative standard deviation of the sphere activity estimates was 16.1% for MC-JOSEM, versus 27.4% for TEW-JOSEM. Additionally, the average relative bias of activity concentration estimates in the liver and the background for MC-JOSEM after 40 iterations was -3.9%, versus -12.2% for TEW-JOSEM, while the average relative standard deviation of these estimates was 2.5% for MC-JOSEM, versus 3.4% for TEW-JOSEM. MC-JOSEM is a promising approach for quantitative activity estimation in 111In SPECT.